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Computer Vision in Construction

Goals

Provide an analysis of computer vision use in construction applications, including cost benefits, market size, best service providers, safety and security purposes, and highest regional uses.

Early Findings

Computer Vision in Construction

  • Computer vision usage for construction purposes can often be implemented at low cost, utilizing already installed camera systems at job sites.
  • Combined with rapidly advancing machine learning processes, computer vision is becoming an accurate and reliable tool for monitoring material quantities and enforcing safety policies without lapses in supervision.
  • Computer vision also shows exceptional utility in measuring manual labor tasks, providing estimates of average individual task durations, and overall project completion times.
  • Job site access can also be monitored by both facial and license plate recognition.
  • Further advancements include the use of drones for computer vision purposes to both monitor sites, and even more accurately measure objects/materials.

Computer Vision in Construction Safety and Security

  • Computer vision can now accurately be used for a wide range of construction safety and security tasks, with capabilities even as far as recognizing the emotional states and fatigue levels of workers to prevent potential issues.
  • It can also provide accurate people-counting services to monitor how many workers are in individual areas, and which authorized personnel are entering and exiting job sites. Motion detection and facial recognition can generate alerts for unauthorized personnel in particular areas.
  • Computer vision can also detect faults in structures that could lead to potentially serious failures that may harm any people in the vicinity of the defect.
  • Since construction has a particularly high injury and fatality rate compared to other industries, approximately one out of five deaths during employment being in the construction field, artificial intelligence through computer vision has enormous potential in protecting workers on job sites.

Proposed next steps:

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